Learning and practicing R with swirl

Swirl Package of R is very good to learn R programming and get into practice with R. However I recommend it to those have knowledge of at least One programming language already.

So lets start.



1. Install R
2. Install RStudio
3. Install swirl package

Go to RStudio console and start with:

install.packages("swirl")

> library(swirl)

| Hi! Type swirl() when you are ready to begin.

> swirl()

| Welcome to swirl! Please sign in. If you've been here before, use the same name as you did then. If you are
| new, call yourself something unique.

What shall I call you? Rajiv

| Thanks, Rajiv. Let's cover a couple of quick housekeeping items before we begin our first lesson. First of
| all, you should know that when you see '...', that means you should press Enter when you are done reading
| and ready to continue.

...  <-- That's your cue to press Enter to continue

| Also, when you see 'ANSWER:', the R prompt (>), or when you are asked to select from a list, that means
| it's your turn to enter a response, then press Enter to continue.

Select 1, 2, or 3 and press Enter 

1: Continue.
2: Proceed.
3: Let's get going!

Selection: 1

| You can exit swirl and return to the R prompt (>) at any time by pressing the Esc key. If you are already
| at the prompt, type bye() to exit and save your progress. When you exit properly, you'll see a short
| message letting you know you've done so.

| When you are at the R prompt (>):
| -- Typing skip() allows you to skip the current question.
| -- Typing play() lets you experiment with R on your own; swirl will ignore what you do...
| -- UNTIL you type nxt() which will regain swirl's attention.
| -- Typing bye() causes swirl to exit. Your progress will be saved.
| -- Typing main() returns you to swirl's main menu.
| -- Typing info() displays these options again.

| Let's get started!

...

| To begin, you must install a course. I can install a course for you from the internet, or I can send you to
| a web page (https://github.com/swirldev/swirl_courses) which will provide course options and directions for
| installing courses yourself. (If you are not connected to the internet, type 0 to exit.)

1: R Programming: The basics of programming in R
2: Regression Models: The basics of regression modeling in R
3: Statistical Inference: The basics of statistical inference in R
4: Exploratory Data Analysis: The basics of exploring data in R
5: Don't install anything for me. I'll do it myself.

Selection: 1
  |====================================================================================================| 100%

| Course installed successfully!


| Please choose a course, or type 0 to exit swirl.

1: R Programming
2: Take me to the swirl course repository!

Selection: 1

| Please choose a lesson, or type 0 to return to course menu.

 1: Basic Building Blocks      2: Workspace and Files        3: Sequences of Numbers    
 4: Vectors                    5: Missing Values             6: Subsetting Vectors      
 7: Matrices and Data Frames   8: Logic                      9: Functions               
10: lapply and sapply         11: vapply and tapply         12: Looking at Data         
13: Simulation                14: Dates and Times           15: Base Graphics           


Selection: 4

  |                                                                                                    |   0%

| The simplest and most common data structure in R is the vector.

...

  |===                                                                                                 |   3%
| Vectors come in two different flavors: atomic vectors and lists. An atomic vector contains exactly one data
| type, whereas a list may contain multiple data types. We'll explore atomic vectors further before we get to
| lists.

...

  |=====                                                                                               |   5%
| In previous lessons, we dealt entirely with numeric vectors, which are one type of atomic vector. Other
| types of atomic vectors include logical, character, integer, and complex. In this lesson, we'll take a
| closer look at logical and character vectors.

...

  |========                                                                                            |   8%
| Logical vectors can contain the values TRUE, FALSE, and NA (for 'not available'). These values are
| generated as the result of logical 'conditions'. Let's experiment with some simple conditions.

...

  |===========                                                                                         |  11%
| First, create a numeric vector num_vect that contains the values 0.5, 55, -10, and 6.

> num_vect <- c(0.5,55,-10,6)

| Keep working like that and you'll get there!

  |=============                                                                                       |  13%
| Now, create a variable called tf that gets the result of num_vect < 1, which is read as 'num_vect is less
| than 1'.

> 
> tf <- num_vect < 1

| You are amazing!

  |================                                                                                    |  16%
| What do you think tf will look like?

1: a single logical value
2: a vector of 4 logical values

Selection: 2

| That's the answer I was looking for.

  |==================                                                                                  |  18%
| Print the contents of tf now.

So, in this way any one can learn R in interactive way